A machine learning algorithm may be able to accurately predict whether or not people with multiple sclerosis (MS) will experience a worsening of disability in the near term — which may help tailor treatment decisions and improve patient quality of life — according to the findings of a new…

Using machine learning to analyze eye scans can help detect slight changes that may be early signs of multiple sclerosis (MS), potentially aiding in early diagnosis of the disease, a study found. The study, “SLO-Net: Enhancing Multiple Sclerosis Diagnosis Beyond Optical Coherence Tomography Using Infrared Reflectance…

Brain atrophy (shrinkage) in people with multiple sclerosis (MS) begins on average more than five years before disease symptoms appear, according to a new study based on machine learning models. “Although the onset of progressive brain tissue loss measured by MRI is not synonymous with the true biological…

A machine learning algorithm that incorporates genetic data alongside clinical and demographic information may be able to more accurately predict the severity of multiple sclerosis (MS), according to a new study. “Once independently validated, the machine learning algorithm could enable clinicians to provide patients with more accurate prognostic information,…

Early Detection of Pseudobulbar Affect May Help Ease MS Symptom I often see posts on social media from people with MS asking if crying for no reason is an MS symptom, because it happens to them. I didn’t know that apparently, it is. Laughing, too. This report says…

A machine learning approach based on eye scans was employed by researchers to diagnose multiple sclerosis (MS) in children with up to 80% accuracy. Optical coherence tomography (OCT) scans also provided enough data to diagnose other demyelinating diseases with 75% accuracy. OCT is an imaging tool that uses…

A new machine learning strategy was able to differentiate tremor specific to multiple sclerosis (MS) from tremor related to other diseases, with more than 90% accuracy, according to a new study. “The proposed method, with high classification accuracy and strong correlations of [tremor] features to clinical outcomes, has clearly…

OM1 has created an artificial intelligence (AI)-based algorithm to estimate scores on the expanded disability status scale (EDSS), an established method for evaluating disability and disease progression in people with multiple sclerosis (MS). The algorithm, using a method called machine learning, was trained to estimate EDSS scores…

Using a two-step machine learning strategy, researchers have developed an algorithm to predict the risk of multiple sclerosis (MS) relapse based on data gleaned from electronic health records. “The two-step machine learning model predicts a patient’s future one-year MS relapse risk with clinically actionable accuracy, comparable to other clinical…

Machine learning — using computer algorithms — can be used to identify people with primary progressive multiple sclerosis (PPMS) who are more likely to respond to treatment, a new study shows. The ability to predict treatment response could allow clinical trials to be designed more efficiently, researchers said. Jean-Pierre…

An increased production of CD25 – an immune receptor that regulates T-cell proliferation and activation – is the most noticeable blood cell immune alteration in people with multiple sclerosis (MS) compared with their unaffected identical twins, a study discovered. The increased CD25 levels, which correlated with disease severity, were…

AB Science OK’d to Start Masitinib Phase 3 Trial for Progressive MS Many of us with multiple sclerosis (MS) have been waiting for another treatment for progressive forms of MS. I hope this brings us another step closer to one. Masitinib is an oral medication that works by blocking…

A new machine learning algorithm — designed to analyze healthcare records — could help in diagnosing multiple sclerosis (MS) sooner by identifying patients’ symptoms earlier. The algorithm, devised by scientists at the University of California San Francisco (UCSF), was described in a study titled “Embedding electronic health records…

Protxx and the University of Victoria are partnering to explore digital biomarkers for multiple sclerosis (MS) that may improve monitoring of disease progression, and facilitate more personalized care and a better quality of life. The digital biomarkers are based on motion vibrations picked up by Protxx’s wearable “phybrata”…

A machine learning-based method that examines walking abnormalities in people with multiple sclerosis (MS) could help identify patients who are at high risk of worsening symptoms, a study suggests. The study, “Predicting Multiple Sclerosis from Gait Dynamics Using an Instrumented Treadmill – A Machine Learning Approach,”…

You’re stressed, and Halo may know it. Halo is a new Amazon service the company says can judge how stressed you are, in part by the tone of your voice. The service uses a wristband that connects to a mobile app. A small sensor in the band monitors temperature, heart…

The upcoming MSVirtual2020 meeting, the largest international conference dedicated to multiple sclerosis (MS) research, will focus on advances and breakthroughs made in MS causes and risk factors, diagnostic tools, treatment response biomarkers, technology, and therapies and interventions. The 8th joint meeting of the Americas Committee for Treatment and…

Researchers developed a way of using machine learning to identify those cells most important for a given function or task, such as movement, and for evaluating how they respond to potentially restorative treatments. Using Augur, as this method is called, the team was able to identify the neural circuits in…

The Australian Government’s Medical Research Future Fund (MRFF) has awarded AU$7.1 million (about $4.95 million) to support two projects focused on harnessing the power of artificial intelligence (AI) and machine learning to develop new ways of diagnosing and treating multiple sclerosis (MS) and mental health disorders in young people.

CorTechs Labs presented new data indicating that machine learning models based on magnetic resonance imaging (MRI) of the brain may aid in the early diagnosis of multiple sclerosis (MS). Company representatives, joined by other experts, also released updated recommendations for a standardized…

Combining data science, artificial intelligence (AI), and machine learning to better identify patterns that may underlie the cause or causes of multiple sclerosis (MS) is the focus of a novel partnership. Despite numerous advances in MS research and treatments, what causes the disease is still unknown. “Given the complexity…

A new clinical application prototype that uses machine learning to help physicians predict the best treatment options for patients with multiple sclerosis (MS) will be unveiled at the American Academy of Neurology’s 2019 annual meeting May 4–10, in Philadelphia, Pennsylvania. The prototype is called PIN Population Data Platform. It has been…

A new web portal called Talk2Me that detects early changes in language could help doctors diagnose or determine progression in neurodegenerative disorders like multiple sclerosis (MS), the scientists who created it suggest. The open platform portal, which gathers language data through an array of cognitive tasks performed…

Novartis and the University of Oxford’s Big Data Institute (BDI) have established an alliance to advance the use of medical data for spotting disease patterns and assessing patients’ responses to treatment. The initiative seeks to enable more informed clinical decision-making and improve the development of treatments for complex diseases.

IQuity, a data analytics company, announced the launch of an analytics platform that uses machine learning to predict, identify, and monitor chronic disease within large populations of patients, including multiple sclerosis (MS). The platform was validated using a pilot study that assessed the healthcare claims of 20 million people…